
AI Innovator
2 days ago
We are seeking an experienced Artificial Intelligence Engineer to join our team. In this role, you will develop and optimize data pipelines using Python, Pandas, and Scikit-learn.
Key Responsibilities:
- Data Pipeline Development: Develop and optimize data pipelines using Python, Pandas, and Scikit-learn.
- Prompt Engineering: Support prompt engineering initiatives for LLM-based applications.
- Model Evaluation: Conduct model evaluation and testing, ensuring accuracy, reliability, and performance.
- Vector Databases: Work with Vector Databases (e.g., Pinecone, FAISS) for embedding storage and retrieval.
Secondary Responsibilities:
- Fine-tuning Models: Assist in fine-tuning small and domain-specific models for production use.
- Automation Scripts: Write automation scripts for data preparation, cleaning, and feature engineering.
- API Integrations: Collaborate with product and engineering teams to enable API integrations for ML services.
Must-Have Skills:
- Python Programming: Strong programming skills in Python with hands-on experience in Pandas and Scikit-learn.
- Prompt Engineering: Basic knowledge of prompt engineering for LLMs.
- Model Evaluation Metrics: Understanding of model evaluation metrics and testing techniques.
- Vector Databases: Exposure to Vector Databases (Pinecone, FAISS, or similar).
Good-to-Have Skills:
- Fine-tuning Models: Experience with fine-tuning smaller ML or LLM models.
- REST APIs: Familiarity with REST APIs / GraphQL and integrating ML models into production workflows.
- Data Preprocessing Pipelines: Knowledge of data preprocessing pipelines and automation scripts.
Soft Skills:
- Problem-solving: Strong problem-solving and analytical mindset.
- Collaboration: Ability to work in a collaborative environment with cross-functional teams.
- Curiosity: Curiosity to explore and learn new AI/ML tools and frameworks.
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